posted on 2021-05-01, 00:00authored byManali Tanna Madhavani
Objectives: This study proposed to evaluate the outcome of implants placed in the UIC COD clinics and assess the various factors that could have resulted in or predicted the health outcome of the implants. The main objectives of the study were to evaluate outcomes of the implants placed at UIC College of Dentistry and identifying factors associated with peri-implant diseases and implant failure. The study also aimed to introduce the use of a novel artificial neural model analysis to predict the most important factors affecting implant survival and implant success. Methods: Axium database was used to collect data for the study. The study consisted of two components. (I) A retrospective component which included evaluation of implants placed between January 1, 2012 to October 31, 2018. (II) A prospective component where the data from the retrospective study was utilized to identify a select set of subjects who received Dentsply OsseoSpeed EV implants during January 1, 2015 to December 31, 2016. Out of this dataset, 36 subjects were randomly selected to perform clinical and radiographic evaluation of the implant(s). Results: The multivariate analysis showed that tobacco smoking, diabetes, history of periodontitis and bone grafting simultaneously with implant placement were significantly associated with peri-implant mucositis (P value <0.05). Results of the artificial neural network model analysis showed that tobacco smoking, patient’s age at the time of implant placement, history of periodontitis and bone grafting prior to or at the time of implant placement are the most important variables predicting implant outcomes (>97% model accuracy. Conclusion: Tobacco smoking, patient’s age at the time of implant placement, history of periodontitis and bone grafting either prior to or at the time of implant placement are the most important predictors for development of peri-implant diseases and implant survival.
Funding: Dentsply Sirona Implants, Sweden
IRB Protocol #: 2018-1552